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Standford AI Report

The takeaways from Stanford’s 386-page report on the state of AI

July 01, 20232 min read

The key takeaways from the article (IMO in italics):

  • AI development has flipped over the last decade from academia-led to industry-led, by a large margin, and this shows no sign of changing. AI has reached prime time

  • It’s becoming difficult to test models on traditional benchmarks and a new paradigm may be needed here. Need lots of good quality data that is hard to come by - data quality, bias free, intelligently and appropriately tagged and scored

  • The energy footprint of AI training and use is becoming considerable, but we have yet to see how it may add efficiencies elsewhere. Short term problem - computer power is still growing exponentially and energy consumption will find solutions

  • The number of “AI incidents and controversies” has increased by a factor of 26 since 2012, which actually seems a bit low. Stand by for a tsunami with easier access but still the same dumb underlying technology. Correlation is not causation, and AI is poor at fact checking its own "hallucination" outpour

  • AI-related skills and job postings are increasing, but not as fast as you’d think.

  • Policymakers, however, are falling over themselves trying to write a definitive AI bill, a fool’s errand if there ever was one. The issue is not legislative rules by rather a shared set of principles and philosophy for the greater good of mankind and our world.

  • Investment has temporarily stalled, but that’s after an astronomic increase over the last decade.

  • More than 70% of Chinese, Saudi, and Indian respondents felt AI had more benefits than drawbacks. Americans? 35%. None of these regimes are ones I seek to promulgate. How do the Europeans think? I find they are more balanced in their weltanschau

For the full report, see: https://techcrunch.com/2023/04/04/the-takeaways-from-stanfords-386-page-report-on-the-state-of-ai/?utm_source=tldrnewsletter

Check out these postings as well as the mozilla's internet principles that might be a good starting point for AI:
https://www.linkedin.com/posts/nicholasseiersen_ai-ethicalai-airisks-activity-7045020782573350912-qx6a?utm_source=share&utm_medium=member_desktop
https://www.linkedin.com/feed/update/urn:li:activity:7045933633458622464?utm_source=share&utm_medium=member_desktop

blog author image

Nick Seiersen

Nick Seiersen is a supply chain veteran from across Europe and the Americas. He has worked on and led over 100 projects across all industries, saving about $1B in costs and assets. Hi motto: Sustainable Supply Chain Value through the Right Deals with the Right Trading Partners

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Data Quality

Standford AI Report

The takeaways from Stanford’s 386-page report on the state of AI

July 01, 20232 min read

The key takeaways from the article (IMO in italics):

  • AI development has flipped over the last decade from academia-led to industry-led, by a large margin, and this shows no sign of changing. AI has reached prime time

  • It’s becoming difficult to test models on traditional benchmarks and a new paradigm may be needed here. Need lots of good quality data that is hard to come by - data quality, bias free, intelligently and appropriately tagged and scored

  • The energy footprint of AI training and use is becoming considerable, but we have yet to see how it may add efficiencies elsewhere. Short term problem - computer power is still growing exponentially and energy consumption will find solutions

  • The number of “AI incidents and controversies” has increased by a factor of 26 since 2012, which actually seems a bit low. Stand by for a tsunami with easier access but still the same dumb underlying technology. Correlation is not causation, and AI is poor at fact checking its own "hallucination" outpour

  • AI-related skills and job postings are increasing, but not as fast as you’d think.

  • Policymakers, however, are falling over themselves trying to write a definitive AI bill, a fool’s errand if there ever was one. The issue is not legislative rules by rather a shared set of principles and philosophy for the greater good of mankind and our world.

  • Investment has temporarily stalled, but that’s after an astronomic increase over the last decade.

  • More than 70% of Chinese, Saudi, and Indian respondents felt AI had more benefits than drawbacks. Americans? 35%. None of these regimes are ones I seek to promulgate. How do the Europeans think? I find they are more balanced in their weltanschau

For the full report, see: https://techcrunch.com/2023/04/04/the-takeaways-from-stanfords-386-page-report-on-the-state-of-ai/?utm_source=tldrnewsletter

Check out these postings as well as the mozilla's internet principles that might be a good starting point for AI:
https://www.linkedin.com/posts/nicholasseiersen_ai-ethicalai-airisks-activity-7045020782573350912-qx6a?utm_source=share&utm_medium=member_desktop
https://www.linkedin.com/feed/update/urn:li:activity:7045933633458622464?utm_source=share&utm_medium=member_desktop

blog author image

Nick Seiersen

Nick Seiersen is a supply chain veteran from across Europe and the Americas. He has worked on and led over 100 projects across all industries, saving about $1B in costs and assets. Hi motto: Sustainable Supply Chain Value through the Right Deals with the Right Trading Partners

Back to Blog

Other Supply Chain Topics

Standford AI Report

The takeaways from Stanford’s 386-page report on the state of AI

July 01, 20232 min read

The key takeaways from the article (IMO in italics):

  • AI development has flipped over the last decade from academia-led to industry-led, by a large margin, and this shows no sign of changing. AI has reached prime time

  • It’s becoming difficult to test models on traditional benchmarks and a new paradigm may be needed here. Need lots of good quality data that is hard to come by - data quality, bias free, intelligently and appropriately tagged and scored

  • The energy footprint of AI training and use is becoming considerable, but we have yet to see how it may add efficiencies elsewhere. Short term problem - computer power is still growing exponentially and energy consumption will find solutions

  • The number of “AI incidents and controversies” has increased by a factor of 26 since 2012, which actually seems a bit low. Stand by for a tsunami with easier access but still the same dumb underlying technology. Correlation is not causation, and AI is poor at fact checking its own "hallucination" outpour

  • AI-related skills and job postings are increasing, but not as fast as you’d think.

  • Policymakers, however, are falling over themselves trying to write a definitive AI bill, a fool’s errand if there ever was one. The issue is not legislative rules by rather a shared set of principles and philosophy for the greater good of mankind and our world.

  • Investment has temporarily stalled, but that’s after an astronomic increase over the last decade.

  • More than 70% of Chinese, Saudi, and Indian respondents felt AI had more benefits than drawbacks. Americans? 35%. None of these regimes are ones I seek to promulgate. How do the Europeans think? I find they are more balanced in their weltanschau

For the full report, see: https://techcrunch.com/2023/04/04/the-takeaways-from-stanfords-386-page-report-on-the-state-of-ai/?utm_source=tldrnewsletter

Check out these postings as well as the mozilla's internet principles that might be a good starting point for AI:
https://www.linkedin.com/posts/nicholasseiersen_ai-ethicalai-airisks-activity-7045020782573350912-qx6a?utm_source=share&utm_medium=member_desktop
https://www.linkedin.com/feed/update/urn:li:activity:7045933633458622464?utm_source=share&utm_medium=member_desktop

blog author image

Nick Seiersen

Nick Seiersen is a supply chain veteran from across Europe and the Americas. He has worked on and led over 100 projects across all industries, saving about $1B in costs and assets. Hi motto: Sustainable Supply Chain Value through the Right Deals with the Right Trading Partners

Back to Blog

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